Assessment Study of ChatGPT-3.5’s Performance on the Final Polish Medical Examination: Accuracy in Answering 980 Questions DOI Open Access

Julia Siebielec,

Michał Ordak,

Agata Oskroba

et al.

Healthcare, Journal Year: 2024, Volume and Issue: 12(16), P. 1637 - 1637

Published: Aug. 16, 2024

The use of artificial intelligence (AI) in education is dynamically growing, and models such as ChatGPT show potential enhancing medical education. In Poland, to obtain a diploma, candidates must pass the Medical Final Examination, which consists 200 questions with one correct answer per question, administered Polish, assesses students' comprehensive knowledge readiness for clinical practice. aim this study was determine how ChatGPT-3.5 handles included exam. This considered 980 from five examination sessions Examination conducted by Center years 2022-2024. analysis field medicine, difficulty index questions, their type, namely theoretical versus case-study questions. average rate achieved hovered around 60% lower (p < 0.001) than score examinees. lowest percentage answers hematology (42.1%), while highest endocrinology (78.6%). showed statistically significant correlation correctness = 0.04). Questions provided incorrect had responses. type analyzed did not significantly affect 0.46). indicates that can be an effective tool assisting passing final exam, but results should interpreted cautiously. It recommended further verify using various AI tools.

Language: Английский

A systematic review of the impact of artificial intelligence on educational outcomes in health professions education DOI Creative Commons
Eva Feigerlová,

Hind Hani,

Ellie Hothersall-Davies

et al.

BMC Medical Education, Journal Year: 2025, Volume and Issue: 25(1)

Published: Jan. 27, 2025

Language: Английский

Citations

4
Generative artificial intelligence in graduate medical education DOI Creative Commons

Ravi Janumpally,

Suparna Nanua,

Andy Ngo

et al.

Frontiers in Medicine, Journal Year: 2025, Volume and Issue: 11

Published: Jan. 10, 2025

Generative artificial intelligence (GenAI) is rapidly transforming various sectors, including healthcare and education. This paper explores the potential opportunities risks of GenAI in graduate medical education (GME). We review existing literature provide commentary on how could impact GME, five key areas opportunity: electronic health record (EHR) workload reduction, clinical simulation, individualized education, research analytics support, decision support. then discuss significant risks, inaccuracy overreliance AI-generated content, challenges to authenticity academic integrity, biases AI outputs, privacy concerns. As technology matures, it will likely come have an important role future but its integration should be guided by a thorough understanding both benefits limitations.

Language: Английский

Citations

2
Preparing for Artificial General Intelligence (AGI) in Health Professions Education: AMEE Guide No. 172 DOI Creative Commons
Ken Masters, Anne Herrmann–Werner, Teresa Festl‐Wietek

et al.

Medical Teacher, Journal Year: 2024, Volume and Issue: 46(10), P. 1258 - 1271

Published: Aug. 8, 2024

Generative Artificial Intelligence (GenAI) caught Health Professions Education (HPE) institutions off-guard, and they are currently adjusting to a changed educational environment. On the horizon, however, is

Language: Английский

Citations

10
Digital competency among pediatric healthcare workers and students: a questionnaire survey DOI

Sangsang Ren,

Weize Xu, Zhi Chen

et al.

World Journal of Pediatrics, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 3, 2025

Language: Английский

Citations

1
Artificial Intelligence in Health Professions Education assessment: AMEE Guide No. 178 DOI
Ken Masters, Heather MacNeill, Jennifer Benjamin

et al.

Medical Teacher, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 15

Published: Jan. 9, 2025

Health Professions Education (HPE) assessment is being increasingly impacted by Artificial Intelligence (AI), and institutions, educators, learners are grappling with AI's ever-evolving complexities, dangers, potential. This AMEE Guide aims to assist all HPE stakeholders helping them navigate the uncertainty before them. Although impetus AI, grounds its path in pedagogical theory, considers range of human responses, then deals types, challenges, AI roles as tutor learner, required competencies. It discusses difficult ethical issues, ending considerations for faculty development technicalities acknowledgment assessment. Through this Guide, we aim allay fears face change demonstrate possibilities that will allow educators harness full potential

Language: Английский

Citations

1
A Symbolic AI Approach to Medical Training DOI Creative Commons
Alessio Bottrighi, Federica Grosso,

Marco Ghiglione

et al.

Journal of Medical Systems, Journal Year: 2025, Volume and Issue: 49(1)

Published: Jan. 9, 2025

Abstract In traditional medical education, learners are mostly trained to diagnose and treat patients through supervised practice. Artificial Intelligence simulation techniques can complement such an educational this paper, we present GLARE-Edu, innovative system in which AI knowledge-based methodologies exploited train “how act” on based the evidence-based best practices provided by clinical practice guidelines. GLARE-Edu is being developed a multi-disciplinary team involving physicians experts, within AI-LEAP (LEArning Personalization of with AI) Italian project. domain-independent: it supports acquisition guidelines case studies computer format. Based acquired (and studies), provides series facilities: (i) navigation , navigate structured representation (ii) automated show how guideline would suggest act, step-by-step, specific case, (iii) (self) verification asking they comparing step-by-step learner’s proposal suggestions proper guideline. describe architecture general features, demonstrate our approach concrete application melanoma propose preliminary evaluation.

Language: Английский

Citations

1
A systematic literature review on the application of generative artificial intelligence (GAI) in teaching within higher education: Instructional contexts, process, and strategies DOI
Peijun Wang, Yuhui Jing, Shusheng Shen

et al.

The Internet and Higher Education, Journal Year: 2025, Volume and Issue: unknown, P. 100996 - 100996

Published: Jan. 1, 2025

Language: Английский

Citations

1
The Role of AI in Reshaping Medical Education: Opportunities and Challenges DOI Open Access
Majid Ali

The Clinical Teacher, Journal Year: 2025, Volume and Issue: 22(2)

Published: Feb. 16, 2025

Artificial intelligence (AI) is redefining medical education, bringing new dimensions of personalized learning, enhanced visualization and simulation-based clinical training to the forefront. Additionally, AI-powered simulations offer realistic, immersive opportunities, preparing students for complex situations fostering interprofessional collaboration skills essential modern healthcare. However, integration AI into education presents challenges, particularly around ethical considerations, skill atrophy due overreliance exacerbation digital divide among educational institutions. Addressing these challenges demands a balanced approach that includes blended learning models, literacy faculty development ensure serves as supplement to, rather than replacement for, core competencies. As evolves alongside AI, institutions must prioritize strategies preserve human-centred while advancing technological innovation prepare future healthcare professionals an AI-enhanced landscape.

Language: Английский

Citations

1
Insights Gained from Using AI to Produce Cases for Problem-Based Learning DOI Creative Commons
Enjy Abouzeid, Patricia Harris

Published: Feb. 27, 2025

Language: Английский

Citations

1
Uso de la inteligencia artificial en la educación médica: ¿herramienta o amenaza? Revisión de alcance DOI Open Access
Mateo Aguirre Flórez, José Fernándo Gómez, Laura Alejandra Jímenez-Osorio

et al.

Investigación en Educación Médica, Journal Year: 2025, Volume and Issue: 14(53), P. 90 - 106

Published: Jan. 5, 2025

Introducción: La inteligencia artificial (IA) ha captado considerable atención entre las tecnologías emergentes. IA se refiere a la capacidad de máquinas para aprender y tomar decisiones autónomas, asemejándose humana. En formación profesionales salud, muestra potencial mejorar enseñanza el aprendizaje. Objetivo: Analizar aplicaciones en médicos, incluyendo sus beneficios, limitaciones e implicaciones éticas sociales. Método: Se realizó una búsqueda bases datos electrónicas como PubMed, EMBASE, Web of Science Google Scholar, utilizando términos MeSH operadores booleanos refinar los estudios. analizaron sintetizaron estudios seleccionados identificar principales médica beneficios asociados. Resultados: identificaron múltiples educación médica, aprendizaje personalizado, retroalimentación inmediata fácil acceso información. Los incluyen mayor eficiencia efectividad del Las consideraciones precauciones sesgo potencial, privacidad seguridad datos, dependencia excesiva tecnología impactos relación médico-paciente. Conclusión: ofrece ventajas significativas mejorando calidad tratamiento oportuno pacientes. Sin embargo, es importante considerar implicaciones. implementación adecuada puede aprovechar mientras mitigan riesgos. médicos deben estar preparados usar manera responsable, equilibrando con cuidado humanista.

Citations

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